The five-number summary of scores on a test is 35 60 65 70 90 Based on this information, there is one outlier. there is more than one outlier. we cannot tell if any outliers are present without seeing the actual observations. there are no outliers.

To determine if there are any outliers in the given data set, we need to calculate the interquartile range (IQR) and then use it to identify any potential outliers.<br /><br />The five-number summary provided is:<br />- Minimum: 35<br />- First Quartile (Q1): 60<br />- Median (Q2): 65<br />- Third Quartile (Q3): 70<br />- Maximum: 90<br /><br />First, we calculate the IQR:<br />\[ \text{IQR} = Q3 - Q1 = 70 - 60 = 10 \]<br /><br />Next, we determine the lower and upper bounds for potential outliers:<br />\[ \text{Lower Bound} = Q1 - 1.5 \times \text{IQR} = 60 - 1.5 \times 10 = 60 - 15 = 45 \]<br />\[ \text{Upper Bound} = Q3 + 1.5 \times \text{IQR} = 70 + 1.5 \times 10 = 70 + 15 = 85 \]<br /><br />Any data points below the lower bound (45) or above the upper bound (85) are considered outliers.<br /><br />Given the data set:<br />\[ 35, 60, 65, 70, 90 \]<br /><br />- 35 is below the lower bound of 45.<br />- 60, 65, and 70 are within the bounds.<br />- 90 is above the upper bound of 85.<br /><br />Therefore, there is one outlier in the data set.<br /><br />The correct answer is:<br />- there is one outlier.